Artificial intelligence in pathologic diagnosis, prognosis and prediction of prostate cancer.

IF 1.5 Q3 UROLOGY & NEPHROLOGY
American journal of clinical and experimental urology Pub Date : 2024-08-25 eCollection Date: 2024-01-01 DOI:10.62347/JSAE9732
Min Zhu, Rasoul Sali, Firas Baba, Hamdi Khasawneh, Michelle Ryndin, Raymond J Leveillee, Mark D Hurwitz, Kin Lui, Christopher Dixon, David Y Zhang
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引用次数: 0

Abstract

Histopathology, which is the gold-standard for prostate cancer diagnosis, faces significant challenges. With prostate cancer ranking among the most common cancers in the United States and worldwide, pathologists experience an increased number for prostate biopsies. At the same time, precise pathological assessment and classification are necessary for risk stratification and treatment decisions in prostate cancer care, adding to the challenge to pathologists. Recent advancement in digital pathology makes artificial intelligence and learning tools adopted in histopathology feasible. In this review, we introduce the concept of AI and its various techniques in the field of histopathology. We summarize the clinical applications of AI pathology for prostate cancer, including pathological diagnosis, grading, prognosis evaluation, and treatment options. We also discuss how AI applications can be integrated into the routine pathology workflow. With these rapid advancements, it is evident that AI applications in prostate cancer go beyond the initial goal of being tools for diagnosis and grading. Instead, pathologists can provide additional information to improve long-term patient outcomes by assessing detailed histopathologic features at pixel level using digital pathology and AI. Our review not only provides a comprehensive summary of the existing research but also offers insights for future advancements.

人工智能在前列腺癌病理诊断、预后和预测中的应用。
组织病理学是诊断前列腺癌的黄金标准,但也面临着巨大的挑战。随着前列腺癌跻身美国和全球最常见的癌症之列,病理学家的前列腺活检数量也随之增加。同时,精确的病理评估和分类对于前列腺癌的风险分层和治疗决策非常必要,这给病理学家带来了更大的挑战。数字病理学的最新进展使组织病理学中采用的人工智能和学习工具变得可行。在这篇综述中,我们将介绍人工智能的概念及其在组织病理学领域的各种技术。我们总结了人工智能病理学在前列腺癌中的临床应用,包括病理诊断、分级、预后评估和治疗方案。我们还讨论了如何将人工智能应用整合到常规病理工作流程中。随着这些技术的快速发展,人工智能在前列腺癌中的应用显然已超越了作为诊断和分级工具的最初目标。相反,病理学家可以利用数字病理学和人工智能评估像素级的详细组织病理学特征,从而提供更多信息,改善患者的长期预后。我们的综述不仅对现有研究进行了全面总结,还为未来的进步提供了见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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